The Autoflow system can be deployed and configured using various options. This document will discuss the possible deployment strategies and configuration options for Autoflow, using only the provided sources.
Deployment Options
Ansible
Ansible can be used to automate the deployment process of Autoflow. According to Opensource.com, Ansible allows you to define the entire deployment process, including tasks, servers, and steps, to avoid falling into common pitfalls. Ansible’s automation can help deploy applications, manage services, and verify application states. (Source: https://opensource.com/article/19/1/automating-deployment-strategies-ansible)
GitLab Auto DevOps
GitLab Auto DevOps offers an automated CI/CD-based workflow that supports the entire software supply chain, including build, test, lint, package, deploy, secure, and monitor applications. Auto DevOps provides a set of ready-to-use templates that serve the vast majority of use cases. (Source: https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
OpenShift GitOps
OpenShift GitOps can be used to automate continuous delivery with Red Hat OpenShift Pipelines and continuous deployment. It allows deploying applications to different environments and promoting from lower to upper environments. (Source: https://developers.redhat.com/articles/2023/05/29/how-use-openshift-gitops-deploy-applications)
Configuration Options
Jenkins
Jenkins can be used to create a custom Release Engine, as described in the article by Jen Krieger. Jenkins can tie together various existing FOSS tools to automate portions of the release process. (Source: https://developers.redhat.com/blog/2014/05/21/building-a-continuous-deployment-engine)
Automated Deployment Analysis (ADA)
ADA evaluates the impact of the deployment by analyzing metrics data, log entries, and the responses of configured HTTP requests. This automated analysis helps build a robust deployment process. (Source: https://pipecd.dev/docs-dev/user-guide/managing-application/customizing-deployment/automated-deployment-analysis)
Manual Intervention
Manual intervention pipelines can be used to restrict deployment, adding a manual approval step for management. This method avoids accidental deployments and provides governance over the production environment and security. (Source: https://developers.redhat.com/articles/2023/02/28/how-manual-intervention-pipeline-restricts-deployment)
Autoflow-specific Configuration
Autoflow-specific configuration options include:
- TiDB: Autoflow uses TiDB as its database. TiDB configuration options can be found in the official documentation. (Source: https://docs.pingcap.com/tidb/stable/configuration-file)
- Redis: Autoflow uses Redis for caching. Redis configuration options can be found in the official documentation. (Source: https://redis.io/commands/config-get)
- FastAPI: Autoflow’s API is built using FastAPI. FastAPI configuration options can be found in the official documentation. (Source: https://fastapi.tiangolo.com/advanced/configuration/)
- Next.js: Autoflow’s web interface is built using Next.js. Next.js configuration options can be found in the official documentation. (Source: https://nextjs.org/docs/api-reference/next.config.js/introduction)
These are the possible deployment options and configuration examples for Autoflow. Each option has its advantages and disadvantages, and the choice of deployment and configuration strategy will depend on the specific requirements and infrastructure of the project.
